Lauren E. Margulieux

1.7k total citations
56 papers, 1.0k citations indexed

About

Lauren E. Margulieux is a scholar working on Computer Science Applications, Developmental and Educational Psychology and Experimental and Cognitive Psychology. According to data from OpenAlex, Lauren E. Margulieux has authored 56 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Computer Science Applications, 33 papers in Developmental and Educational Psychology and 9 papers in Experimental and Cognitive Psychology. Recurrent topics in Lauren E. Margulieux's work include Teaching and Learning Programming (37 papers), Innovative Teaching and Learning Methods (27 papers) and Online Learning and Analytics (26 papers). Lauren E. Margulieux is often cited by papers focused on Teaching and Learning Programming (37 papers), Innovative Teaching and Learning Methods (27 papers) and Online Learning and Analytics (26 papers). Lauren E. Margulieux collaborates with scholars based in United States, New Zealand and Ireland. Lauren E. Margulieux's co-authors include Richard Catrambone, Mark Guzdial, Briana B. Morrison, Adrienne Decker, Barbara Ericson, Jochen Rick, Paul Denny, Brett A. Becker, James Prather and Dastyni Loksa and has published in prestigious journals such as Communications of the ACM, Cognitive Science and Educational Psychology Review.

In The Last Decade

Lauren E. Margulieux

51 papers receiving 978 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Lauren E. Margulieux United States	17	748	497	206	176	166	56	1.0k
Briana B. Morrison United States	18	788 1.1×	484 1.0×	216 1.0×	151 0.9×	185 1.1×	67	1.0k
Thomas Price United States	19	802 1.1×	429 0.9×	246 1.2×	312 1.8×	277 1.7×	72	1.4k
Collin Lynch United States	14	543 0.7×	443 0.9×	167 0.8×	519 2.9×	220 1.3×	91	1.0k
Brian Dorn United States	17	539 0.7×	276 0.6×	172 0.8×	87 0.5×	162 1.0×	42	735
Satabdi Basu United States	15	1.0k 1.4×	623 1.3×	153 0.7×	148 0.8×	212 1.3×	33	1.2k
Marcelo Worsley United States	17	681 0.9×	528 1.1×	186 0.9×	299 1.7×	265 1.6×	63	1.1k
Quinn Burke United States	15	674 0.9×	446 0.9×	161 0.8×	53 0.3×	237 1.4×	37	938
Marie Bienkowski United States	12	545 0.7×	492 1.0×	136 0.7×	290 1.6×	155 0.9×	42	1.1k
Jesús Moreno-León Spain	18	1.0k 1.3×	485 1.0×	215 1.0×	153 0.9×	143 0.9×	35	1.1k

Countries citing papers authored by Lauren E. Margulieux

Since Specialization

Citations

This map shows the geographic impact of Lauren E. Margulieux's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lauren E. Margulieux with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lauren E. Margulieux more than expected).

Fields of papers citing papers by Lauren E. Margulieux

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lauren E. Margulieux. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lauren E. Margulieux. The network helps show where Lauren E. Margulieux may publish in the future.

Co-authorship network of co-authors of Lauren E. Margulieux

This figure shows the co-authorship network connecting the top 25 collaborators of Lauren E. Margulieux. A scholar is included among the top collaborators of Lauren E. Margulieux based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lauren E. Margulieux. Lauren E. Margulieux is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Margulieux, Lauren E., et al.. (2025). Programming Self-Efficacy in CS: Adding Four Areas of Validity to the Steinhorst Instrument. 213–219. 1 indexed citations

Margulieux, Lauren E., et al.. (2025). CS Concepts and Contextual Factors in Integrated Computing Activities in U.S. Schools. 931–937.

Margulieux, Lauren E., et al.. (2025). Building Bridges, Breaking Barriers: Exploring the Dynamics and Key Factors Shaping Computer Science Education Pathways in Teacher Preparation. 33(1). 5–35.

Margulieux, Lauren E., James Prather, Brent N. Reeves, et al.. (2024). Self-Regulation, Self-Efficacy, and Fear of Failure Interactions with How Novices Use LLMs to Solve Programming Problems. Aaltodoc (Aalto University). 276–282. 18 indexed citations

Margulieux, Lauren E., et al.. (2024). Applying CS0/CS1 Student Success Factors and Outcomes to Biggs' 3P Educational Model. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1168–1174. 2 indexed citations

Parkinson, Jack & Lauren E. Margulieux. (2024). Improving CS Performance by Developing Spatial Skills. Communications of the ACM. 68(1). 68–75. 1 indexed citations

Parker, Miranda C., et al.. (2023). Toward CS1 Content Subscales: A Mixed-Methods Analysis of an Introductory Computing Assessment. Digital Archive @ GSU. 1–13. 2 indexed citations

Margulieux, Lauren E., et al.. (2023). Levels of Programming Concepts Used in Computing Integration Activities across Disciplines. 31(2). 167–202. 2 indexed citations

Loksa, Dastyni, Lauren E. Margulieux, Brett A. Becker, et al.. (2022). Metacognition and Self-Regulation in Programming Education: Theories and Exemplars of Use. ACM Transactions on Computing Education. 22(4). 1–31. 65 indexed citations

10.

Yadav, Aman, Cornelia Connolly, Marc Berges, et al.. (2022). A Review of International Models of Computer Science Teacher Education. Data Archiving and Networked Services (DANS). 65–93. 16 indexed citations

11.

Cohen, Jonathan, Lauren E. Margulieux, Maggie Renken, & W. Monty Jones. (2020). Conclusions From the Validation of a Vignette-Based Instrument to Measure Maker Mindsets.. ICLS. 1 indexed citations

12.

Margulieux, Lauren E., et al.. (2019). Review of measurements used in computing education research and suggestions for increasing standardization. Computer Science Education. 29(1). 49–78. 50 indexed citations

13.

Cohen, Jonathan, et al.. (2018). Measuring Maker Mindset: Establishing Content Validity with Card Sorting.. ICLS. 2 indexed citations

14.

Margulieux, Lauren E. & Richard Catrambone. (2017). Using Learners' Self-Explanations of Subgoals to Guide Initial Problem Solving in App Inventor. 21–29. 16 indexed citations

15.

Margulieux, Lauren E. & Richard Catrambone. (2016). Using subgoal learning and self-explanation to improve programming education. Cognitive Science. 5 indexed citations

16.

Margulieux, Lauren E., Briana B. Morrison, Mark Guzdial, & Richard Catrambone. (2016). Training learners to self-explain: Designing instructions and examples to improve problem solving. ScholarWorks - Georgia State University (Georgia State University). 98–105. 3 indexed citations

17.

Morrison, Briana B., Lauren E. Margulieux, Barbara Ericson, & Mark Guzdial. (2016). Subgoals Help Students Solve Parsons Problems. 42–47. 66 indexed citations

18.

Margulieux, Lauren E., Wendy McCracken, & Richard Catrambone. (2015). Mixing in-class and online learning: Content meta-analysis of outcomes for hybrid, blended, and flipped courses. Computer Supported Collaborative Learning. 6 indexed citations

19.

Margulieux, Lauren E. & Richard Catrambone. (2014). Improving Programming Instruction with Subgoal Labeled Instructional Text. Cognitive Science. 36(36). 5 indexed citations

20.

Margulieux, Lauren E., Richard Catrambone, & Mark Guzdial. (2013). Subgoal Labeled Worked Examples Improve K-12 Teacher Performance in Computer Programming Training. Cognitive Science. 35(35). 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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